🛠 Tech Stack

💼 About This Role

You'll architect and lead the infrastructure strategy for our next-generation Production ML platform on Google Cloud. Your core impact will be building the "paved road" that automates everything from model deployment to networking, ensuring elastic, secure, and resilient systems. Join a high-trust, outcome-focused team solving challenging ML problems.

🎯 What You'll Do

• Design and deploy elastic scaling cloud infrastructure on GCP with Kubernetes.
• Build and maintain CI/CD pipelines for ML model training, testing, and deployment.
• Implement observability tools for model drift, accuracy, and latency tracking.
• Bridge the gap between data, ML, backend, and frontend engineering teams.
• Participate in on-call rotation and ensure SOC compliance.

📋 Requirements

• 8-10+ years in DevOps/Platform Engineering
• At least 2 years operating production ML workloads
• Deep hands-on experience with GCP and GKE
• Expert-level Terraform with GitOps workflow

✨ Nice to Have

• Experience with ML observability for model accuracy and drift
• Ansible for cluster bootstrap and recovery
• Kubernetes (CKA/CKS) or GCP certifications

🎁 Benefits & Perks

• 🚀 Solve real customer problems with immediate impact
• 👁️ See your impact in a scrappy, nimble organization
• 📈 Accelerate your career learning new technologies and markets
• 🤝 Work with talented people in a growth-oriented environment

📨 Hiring Process

Estimated timeline: 3-5 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3System Design Interview· 60 min
4. 4Hiring Manager Interview· 45 min
5. 5Offer· 15 min